Presented with Google Analytics’ rich data, it’s easy for marketers to get overwhelmed or distracted. There’s a fine line, after all, between simply collecting dots and actually connecting them.
Google Analytics can grant tremendous insight into customer behavior. But extracting that information is impossible unless you know what to look for. Measurement is the first step towards improvement, but it’s far from the only step. Getting the most out of Google Analytics requires setting strategic goals, connecting them to measurable values, then interpreting those results into actionable insights.
By following a few key tips and tricks, marketers can utilize Google Analytics to optimize their customer outreach and drive conversions. Here’s how to squeeze the most value out of the platform.
Clarify Customer Journeys with Custom Dimensions
Hard as it is to believe, Google Analytics dashboards only display a fraction of the total data gathered. Want proof? When exporting Analytics data for BigQuery (Google’s premium Cloud service offering), Google Analytics includes multiple Custom Dimensions that its regular users never get to see.
Dimensions are the measurements Google Analytics use to describe objects (e.g. a dimension of the object “session” might be “session duration”). These measurements serve as the building blocks of all possible metrics (e.g. a metric could be “average session duration”). Google Developer Expert Simo Ahava explains that adding just a few dimensions opens an entire universe of new measurement possibilities for tracking customer journeys. He suggests marketers employ four distinct levels of aggregation: Hit Timestamp, User ID, Session ID and Client ID.
The ability to drill down to the level of individual hits and sessions can generate eye-opening insights about how customers interact with your site. One example is tracing successful paths to purchases and looking for patterns and trends.
Custom Dimensions like Session ID assign all hits within a given session a unique identifier, enabling marketers to sort by sessions that ended in a conversion by seeing each page a customer visited along the way. Hit Timestamp tags every single hit with a time-zone adjusted marker, letting marketers pinpoint the exact timing of each step towards conversion. Google Client ID tracks users not logged in and identifies attributes like browser and device, shedding light on where they were visiting from. And User ID tracks individual users across sessions, giving an even wider perspective on the broader path to purchase.
Analyzing successful customer journeys is just one use-case for Custom Dimensions, but the possibilities they afford are almost limitless. Custom Dimensions allow seamless tracking of customer journeys, helping marketers better understand what went well, in addition to what didn’t go as planned.
Use Non-Converting Sessions as Learning Opportunities
Great digital marketers don’t just admit their mistakes, they analyze them in detail.
Focusing only on converting sessions likely means that the vast majority of your overall user data is being overlooked. Segment non-converting sessions and regularly investigate them for common points of drop-off or friction, and marketers are sure to find new opportunities for optimization or fixing nagging UI/UX bugs.
Although Google Analytics is a powerful tool all on its own, connecting GA parameters such as Client ID to third-party apps will allow even greater fidelity in pinpointing customer pain-points and optimizing user experience. Session recording services like HotJar or Lucky Orange provide deeper insight into what users experience when visiting your site. These services also offer real videos of individual user behavior and aggregate this interaction data into detailed heatmaps. Tools like these provide excellent supplements to standard analytics. While simple metrics like bounce-rate might hint at a problem, seeing the frustration play out on video will make diagnosing and addressing the issue crystal clear.
Always Double-Check Metrics for Discrepancies
In addition to supplementing standard metrics, third-party tools allow marketers to confirm the accuracy of Google Analytics’ measurements. For example, sometimes a session Google Analytics reported as a bounce will appear to be a meaningful engagement when reviewing the video of the interaction.
Inaccurate behavior metrics like this can be the result of improper code implementation (this is particularly true for calculated metrics like “Bounce Rate”), which is why marketers should always monitor these metrics for discrepancies. However, if no coding errors are found and there are still false-positive bounces, it might be time to set up adjusted bounce rate.
Adjusted bounce rate is a commonly overlooked metric that fills many of the gaps left by regular bounce rate alone. Especially when measuring interactions on standalone content like blog posts, regular bounce rate can be downright misleading. Imagine that someone came to your site, read the entire post and left happy. That interaction would still register as a regular bounce, even though the visitor meaningfully engaged.
Unlike regular bounce rate, adjusted bounce rate lets marketers define a specific duration after which a user counts as “engaged” no matter what. Turning on adjusted bounce rate can lead to a shocking drop in total bounces and a bump in other metrics like session duration. The lesson: fine-tuning measurement and evaluation criteria can help to clarify the big picture.
Blend Data to Help Visualize the Bigger Picture
Combing through granular data is essential for formulating an optimal marketing strategy but is impractical when it comes to tracking success day-to-day. Once you’ve identified the most important questions worth answering, the next step is to select metrics to serve as key performance indicators (KPIs). Due to the variety of data sources and types, and the complexity of variables affecting site performance, KPIs only factoring a single metric are rarely effective. The best strategy is to intelligently combine relevant data points into blended metrics you can follow at a glance.
Luckily, Google Data Studio is a free tool that integrates with over 500 user data sources and allows marketers to blend metrics then track and display them using customizable dashboards. Google Data Studio has native support for Google Analytics to measure and chart all of the chosen custom segments and dimensions. What’s even better is the ability to link data from YouTube videos, Facebook ads and more, then tinker with the interplay and attribution between data from these disparate platforms. The most important feature, though, is having all your custom-blended KPIs displayed and updated in real-time. This maximizes the likelihood of making decisions based on the data you’ve spent all this effort analyzing and collecting.
Using all the tips and strategies highlighted above will enable marketers to tap the nearly limitless potential of Google Analytics, and empower brands to start wielding this powerful tool to make more informed decisions, improve site performance and achieve truly remarkable results.